An inertial measurement unit (IMU) is a closed system that is used to detect changes in angular rate and velocity. As a closed system it is used to detect attitude and motion changes, and can be employed to determine the motion of a carrier, such as aircraft, and geo-location measurements on sensor equipment, wearable computing, e.g., as in movement detection measurements of soldiers operating on the ground, and camera stabilization platforms. A conventional IMU detects acceleration and rate of change in attitude (i.e., roll, pitch, and yaw rates) and measures these parameters over time to find the total change from the initial position. A conventional IMU is not an inertial navigation system, since it does not know its own location, but an extended IMU can provide additional data such as velocity, position, heading attitude, pitch, roll, angular rates, and acceleration with inherent error correction, with accuracies many orders of magnitude greater than that of an inertial navigation unit.
An IMU does not detect linear velocity and position directly, which are computed parameters, by integration and double integration, based on measured accelerations, angular rates, and initial conditions. Small errors in acceleration can cause large errors in velocity and position.
Conventional IMUs are generally associated with high cost, large bulk, high power consumption, limited lifetime, and long turn-on time. The high cost and large size in particular have generally precluded application of IMUs to technologies such as geolocation measurements on sensor equipment; wearable computing (e.g., in movement detection measurements of soldiers operating on the ground), and camera stabilization platforms.
Other difficulties with convention IMUs include accumulated error, since the IMU is continually adding detected changes to the current position, and any error in the measurement is cumulative, leading to “drift.” Such drift can comprise in a range of 100-200 deg/h.
Navigation systems can also employ global positioning satellite (GPS) system to correct for long-term drift in position determination by the IMU.
Micro Electro-Mechanical System (MEMS) technology has resulted in the development of a micro, low-cost IMU that comprises MEMS angular rate and acceleration sensors on silicon chips. However, despite their enormous cost, size, weight, thermal stability, and wide dynamic range advantages over conventional inertial sensors, the MEMS IMUs generally yield less precise and accurate measurements relative to their conventional IMU counterparts.
It is also known to use a high-precision positioning and data integrated system comprising a MEMS IMU, two GPS systems providing raw data, and a centralized processing module that comprises Kalman filter integration to correct various measurement errors such as tilt angle shifts, velocity error, and accelerometer errors received by the device's navigation module. However, GPS systems may be blocked by obstructions, thereby reducing the effectiveness of the system.
The concept of a “virtual gyro” has also been explored, wherein gyroscopes are replaced with an array of relatively inexpensive accelerometers. The system comprises distributed accelerometers combined with a multiple-antenna, GPS-based, attitude-determination system. In this system, however, accelerometer noise is known to be a major source of error in both angular and linear parameters.
One critical cause of error in position measurement is error in the orientation determined by the gyros. This is so because the maturity of MEMS accelerometers, now in the 100-mg class, has put extreme pressure on the pitch and roll accuracy to reach the same level of performance, which is far more difficult for the gyros than for the accelerometers.
While the invention disclosed in the parent '402 patent advanced the field of IMUs significantly, further testing determined that additional algorithm and packaging improvements would be required in order that the device meet certain predetermined criteria for accuracy and robustness when used under extreme conditions. Therefore, it would be advantageous to provide an improved algorithm suite and improved packaging for an IMU for use, for example, in such extreme conditions.